This invention relates generally to Nuclear Medicine imaging systems, and more particularly, to processing data acquired by imaging systems having multiple stationary detectors.
Traditional Nuclear Medicine imaging systems use a small number of large image detectors, such as one, two or three detectors, to acquire imaging data. The image detectors are rotated about a patient to acquire a plurality of projections to create a multi-dimensional image of a structure of interest. For example, 40, 60 or more projections may be acquired. This is very time consuming and requires the patient to lie motionless for an extended period of time. Moreover, the imaging system must comprise a gantry capable of rotating the heavy detectors about the patient.
Using the traditional imaging system, a single detector may be rotated over 180 degrees to acquire 60 projections, each of which is separated by 3 degrees. The detector is positioned at a first position, a first image is acquired, the detector is moved to a second position, a second image is acquired, and so on. Each image produces a 2D representation and has a known symmetry with respect to the other images. Iterative reconstruction algorithms known in the art may then use information about the physical construction and properties of the imaging system to reconstruct the dataset into 3D and/or 4D representations.
Iterative algorithms are computationally intensive and require more computing power and time than what is generally available and acceptable with a current imaging system. Iterative processing takes the full dataset and processes all of the data a number of times, such as twenty times, which is very resource and time intensive. Therefore, techniques such as Ordered Sub-set Expectation Maximization (OSEM) have been developed for accelerating iterative reconstruction algorithms. Ordered Sub-set (OS) methods are based on performing at least the first few iterations (and optionally most or all of the iterations) on a smaller sub-set of the total available dataset. It is important for the conversion of the iterative process that the symmetry of the sub-set be similar to the symmetry of the dataset as a whole.
In the example above, the data may be arranged as a set of angular 2D projections. Using the OS algorithm, the projections within the dataset may be divided into five sub-sets. A first sub-set contains projections 1, 6, 11, . . . , and 56 taken at 3, 18, 33, . . . degrees. A second sub-set contains projections 2, 7, 12, . . . , and 57. Continuing the pattern, a fifth sub-set contains projections 5, 10, 15, . . . , and 60. As each iteration is performed using one sub-set which is a portion of the total dataset, the computation time is shorter.
Imaging systems having multiple smaller-sized detectors are desirable as patient data can be acquired more quickly. The multiple detectors are arranged around a patient and acquire data of the anatomy of interest simultaneously. Unfortunately, the datasets do not have the simple symmetry of projection as discussed above, and thus the algorithms previously used for acceleration of the iterative processing do not apply. Also, the total number of detectors may not produce as rich a dataset as was previously acquired in the 60-90 projections.
Therefore, a need exists for system and methods of iterative processing that may be used with imaging systems acquiring data using multiple stationary detectors. Certain embodiments of the present invention are intended to meet these needs and other objectives that will become apparent from the description and drawings set forth below.